Nicolai, TimTimNicolaiHaring, MarkMarkHaringGrøtli, Esten I.Esten I.GrøtliGravdahl, Jan T.Jan T.GravdahlReger, JohannJohannReger2024-01-182024-01-182023https://publica.fraunhofer.de/handle/publica/45899510.23919/ECC57647.2023.10178224This paper considers the realization of discrete-time linear time-invariant dynamical systems using input-output data. Starting from a generalized state-space representation that accounts for static offsets, a state-independent system representation is derived using the Cayley-Hamilton theorem and characteristic parameters are introduced to describe the system dynamics in an alternative way. Given input-output data, we present two formulations to address model deviations and to identify characteristic parameters by minimizing considered error terms in a least squares sense. The applicability of the proposed subspace identification method is demonstrated with physical data of the identification database DaISy.enLinear systemsParameter estimationSystem dynamicsDatabasesFilteringMathematical modelsObject recognitionDDC::500 Naturwissenschaften und Mathematikconference paper